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Using Artificial Intelligence to Better Understand Human Intelligence

Gordon Pennycook et al.

Current Directions in Psychological Science2026https://doi.org/10.1177/09637214261417960article
AJG 4
Weight
0.50

What the paper says

A consistent pattern emerges from the history of psychology: Technological advances change the way that we understand ourselves. We argue that, in addition to various uses that are already common (e.g., qualitative coding), large language models can be integrated into survey software and act as a virtual research assistant that can generate tailored stimuli on the fly. This creates unprecedented flexibility in developing materials for psychological theory testing. We present an illustrative case study to show how a major lingering debate in the field—that is, whether people really change their mind according to evidence or, instead, rely on motivated reasoning—was pushed forward by using artificial intelligence (AI) to administer personalized experimental treatments. We discuss various potential uses of AI to test hypotheses in psychological science and argue that psychologists should seriously consider using AI to better understand human intelligence.

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https://doi.org/https://doi.org/10.1177/09637214261417960

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@article{gordon2026,
  title        = {{Using Artificial Intelligence to Better Understand Human Intelligence}},
  author       = {Gordon Pennycook et al.},
  journal      = {Current Directions in Psychological Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/09637214261417960},
}

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Using Artificial Intelligence to Better Understand Human Intelligence

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.